Recent developments in metamodel based robust black-box simulation optimization: an overview
In the real world of engineering problems, in order to reduce optimization costs in physical processes, running simulation experiments in the format of computer codes have been conducted. It is desired to improve the validity of simulation-optimization results by attending the source...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/81942/1/Recent%20developments%20in%20metamodel%20based%20robust%20black-box%20simulation%20optimization.pdf |
| _version_ | 1796980978740101120 |
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| author | Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah Ebrahim, Nader Ale |
| author_facet | Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah Ebrahim, Nader Ale |
| author_sort | Parnianifard, Amir |
| collection | UPM |
| description | In the real world of engineering problems, in order to reduce optimization costs in physical processes, running simulation experiments in the format of computer codes have been conducted. It is desired to improve the validity of simulation-optimization results by attending the source of variability in the model’s output(s). Uncertainty can increase complexity and computational costs in Designing and Analyzing of Computer Experiments (DACE). In this state-of the art review paper, a systematic qualitative and quantitative review is implemented among Metamodel Based Robust Simulation Optimization (MBRSO) for black-box and expensive simulation models under uncertainty. This context is focused on the management of uncertainty, particularly based on the Taguchi worldview on robust design and robust optimization methods in the class of dual response methodology when simulation optimization can be handled by surrogates. At the end, while both trends and gaps in the research field are highlighted, some suggestions for future research are directed. |
| first_indexed | 2024-03-06T10:31:00Z |
| format | Article |
| id | upm.eprints-81942 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:31:00Z |
| publishDate | 2019 |
| publisher | Growing Science |
| record_format | dspace |
| spelling | upm.eprints-819422021-08-12T23:07:30Z http://psasir.upm.edu.my/id/eprint/81942/ Recent developments in metamodel based robust black-box simulation optimization: an overview Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah Ebrahim, Nader Ale In the real world of engineering problems, in order to reduce optimization costs in physical processes, running simulation experiments in the format of computer codes have been conducted. It is desired to improve the validity of simulation-optimization results by attending the source of variability in the model’s output(s). Uncertainty can increase complexity and computational costs in Designing and Analyzing of Computer Experiments (DACE). In this state-of the art review paper, a systematic qualitative and quantitative review is implemented among Metamodel Based Robust Simulation Optimization (MBRSO) for black-box and expensive simulation models under uncertainty. This context is focused on the management of uncertainty, particularly based on the Taguchi worldview on robust design and robust optimization methods in the class of dual response methodology when simulation optimization can be handled by surrogates. At the end, while both trends and gaps in the research field are highlighted, some suggestions for future research are directed. Growing Science 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81942/1/Recent%20developments%20in%20metamodel%20based%20robust%20black-box%20simulation%20optimization.pdf Parnianifard, Amir and Ahmad, Siti Azfanizam and Mohd Ariffin, Mohd Khairol Anuar and Ismail, Mohd Idris Shah and Ebrahim, Nader Ale (2019) Recent developments in metamodel based robust black-box simulation optimization: an overview. Decision Science Letters, 8 (1). pp. 17-44. ISSN 1929-5804; ESSN: 1929-5812 http://growingscience.com/beta/dsl/2812-recent-developments-in-metamodel-based-robust-black-box-simulation-optimization-an-overview.html 10.5267/j.dsl.2018.5.004 |
| spellingShingle | Parnianifard, Amir Ahmad, Siti Azfanizam Mohd Ariffin, Mohd Khairol Anuar Ismail, Mohd Idris Shah Ebrahim, Nader Ale Recent developments in metamodel based robust black-box simulation optimization: an overview |
| title | Recent developments in metamodel based robust black-box simulation optimization: an overview |
| title_full | Recent developments in metamodel based robust black-box simulation optimization: an overview |
| title_fullStr | Recent developments in metamodel based robust black-box simulation optimization: an overview |
| title_full_unstemmed | Recent developments in metamodel based robust black-box simulation optimization: an overview |
| title_short | Recent developments in metamodel based robust black-box simulation optimization: an overview |
| title_sort | recent developments in metamodel based robust black box simulation optimization an overview |
| url | http://psasir.upm.edu.my/id/eprint/81942/1/Recent%20developments%20in%20metamodel%20based%20robust%20black-box%20simulation%20optimization.pdf |
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